CLASSIFICATION METHOD BASED ON SUPPORT VECTOR MACHINE

摘要

Provided is a classification method based on a support vector machine, which is effective for a small amount of training data. The classification method based on a support vector machine includes building a first classification model by applying a weight value based on a geometrical distribution of an input feature vector, building a second classification model, based on a classification uncertainty of the input feature vector, and merging the first classification model and the second classification model to perform dual optimization.